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Age and Gender Recognition on Imbalanced Dataset of Face Images with Deep Learning

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Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19) (IITI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1156))

Abstract

The paper describes usage of deep neural networks based on ResNet and Xception architectures for recognition of age and gender of imbalanced dataset of face images. Described dataset collection process from open sources. Training sample contains more than 210000 images. Testing sample have more 1700 special selected face images with different ages and genders. Training data has imbalanced number of images per class. Accuracy for gender classification and mean absolute error for age estimation are used to analyze results quality. Age recognition is described as classification task with 101 classes. Gender recognition is solved as classification task with two categories. Paper contains analysis of different approaches to data balancing and their influence to recognition results. The computing experiment was carried out on a graphics processor using NVidia CUDA technology. The average recognition time per image is estimated for different deep neural networks. Obtained results can be used in software for public space monitoring, collection of visiting statistics etc.

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Acknowledgment

The research was made possible by Government of the Russian Federation (Agreement № 075-02-2019-967).

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Authors and Affiliations

  1. Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Institutskiy per., 9, Moscow, 141700, Russia

    Dmitry Yudin

  2. Belgorod State Technological University named after V.G. Shukhov, Kostukova str. 46, Belgorod, 308012, Russia

    Maksim Shchendrygin & Alexandr Dolzhenko

Authors
  1. Dmitry Yudin
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  2. Maksim Shchendrygin
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  3. Alexandr Dolzhenko
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Corresponding author

Correspondence to Dmitry Yudin .

Editor information

Editors and Affiliations

  1. Rostovskogo Strelkovogo Polka Narodnogo, Rostov State Transport University, Rostov-on-Don, Russia

    Sergey Kovalev

  2. Bauman Moscow State Technical University, Moscow, Russia

    Valery Tarassov

  3. Department of Computer Science, VSB-Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Vaclav Snasel

  4. Rostovskogo Strelkovogo Polka, Rostov State Transport University, Rostov-on-Don, Russia

    Andrey Sukhanov

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Yudin, D., Shchendrygin, M., Dolzhenko, A. (2020). Age and Gender Recognition on Imbalanced Dataset of Face Images with Deep Learning. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_4

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